AIMC Topic: Animals

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A disector-based framework for the automatic optical fractionator.

Journal of chemical neuroanatomy
Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep ...

Human Gait Analysis: A Sequential Framework of Lightweight Deep Learning and Improved Moth-Flame Optimization Algorithm.

Computational intelligence and neuroscience
Human gait recognition has emerged as a branch of biometric identification in the last decade, focusing on individuals based on several characteristics such as movement, time, and clothing. It is also great for video surveillance applications. The ma...

Fully body visual self-modeling of robot morphologies.

Science robotics
Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying th...

New insights in improving sustainability in meat production: opportunities and challenges.

Critical reviews in food science and nutrition
Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of co...

Feasibility study of three-material decomposition in dual-energy cone-beam CT imaging with deep learning.

Physics in medicine and biology
In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different material distribution volumes from the dual-energy CBCT projection data.In Trip...

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Sensors (Basel, Switzerland)
Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and harvesting fish, while still being environmentally friendly. The proposed 2D computer vision method is aimed at non-intrusively estimating the weight o...

The immuneoreaction and antioxidant status of Chinese mitten crab (Eriocheir sinensis) involve protein metabolism and the response of mTOR signaling pathway to dietary methionine levels.

Fish & shellfish immunology
To study the effects of dietary methionine on growth performance, immunity, antioxidant capacity, protein metabolism, inflammatory response and apoptosis factors in Chinese mitten crabs (Eriocheir sinensis). Five diets with different methionine level...

Gene function prediction in five model eukaryotes exclusively based on gene relative location through machine learning.

Scientific reports
The function of most genes is unknown. The best results in automated function prediction are obtained with machine learning-based methods that combine multiple data sources, typically sequence derived features, protein structure and interaction data....

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting.

Physics in medicine and biology
Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multiforme (GBM) tumor-bearing small animals without incurring x-ray radiation burden. However, the use of this imaging modality is limited due to photon sca...

Deep learning versus iterative reconstruction on image quality and dose reduction in abdominal CT: a live animal study.

Physics in medicine and biology
While simulated low-dose CT images and phantom studies cannot fully approximate subjective and objective effects of deep learning (DL) denoising on image quality, live animal models may afford this assessment. This study is to investigate the potenti...